Export Reviews, Discussions, Author Feedback and Meta-Reviews

This paper addresses the problem of learning causal networks with interventions, when each intervention is limited to size k. The paper is generally well-written and addresses a relevant question, as it is generally not feasible to learn the causal structure from observational data alone. Moreover, in some cases, it may also not be possible to perform arbitrarily large interventions, but it is possible to perform interventions over smaller subsets of the variables. The authors prove a number of results around the number of interventions required to learn complete and chordal graphs, and, while I was not able to check all the proofs in detail, the results are as expected (and appear to be correct). The results on chordal graphs are applicable to general causal structures in the sense that application of conditional independence learning and Meek rules results in a chain graph with chordal chain components.